Citation:Marisaldi, M., et al. (2014) • latitude band and selected to have the maximum photon energy up to 30 MeV. The characteristics of the AGILE events are analyzed and compared to the observational framework established by the two other currently active missions capable of detecting TGFs from space, RHESSI and Fermi. A detailed model of the MCAL dead time is presented, which is fundamental to properly interpret our observations. The most significant contribution to dead time is due to the anticoincidence shield in its current configuration and not to the MCAL detector itself. Longitude and local time distributions are compatible with previous observations, while the duration distribution is biased toward longer values because of dead time. The intensity distribution is compatible with previous observations, when dead time is taken into account. The TGFs cumulative spectrum supports a low production altitude, in agreement with previous measurements. We also compare our sample to lightning sferics detected by the World Wide Lightning Location Network and suggest a new method to assess quantitatively the consistency of two TGF populations based on the comparison of the associated lightning activity. According to this method, AGILE and RHESSI samples are compatible with the same parent population. The AGILE TGF catalog below 30 MeV is accessible online at the website of the ASI Science Data Center http://www.asdc.asi.it/mcaltgfcat/.

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At the end of March 2015 the onboard software configuration of the Astrorivelatore Gamma a Immagini Leggero (AGILE) satellite was modified in order to disable the veto signal of the anticoincidence shield for the minicalorimeter instrument. The motivation for such a change was the understanding that the dead time induced by the anticoincidence prevented the detection of a large fraction of Terrestrial Gamma‐Ray Flashes (TGFs). The configuration change was highly successful resulting in an increase of one order of magnitude in TGF detection rate. As expected, the largest fraction of the new events has short duration (<100 μs), and part of them has simultaneous association with lightning sferics detected by the World Wide Lightning Location Network. The new configuration provides the largest TGF detection rate surface density (TGFs/km2/yr) to date, opening prospects for improved correlation studies with lightning and atmospheric parameters on short spatial and temporal scales along the equatorial region.

[1] Subionospheric VLF recordings are investigated in relation with intense cloud-to-ground (CG) lightning data. Lightning impacts the lower ionosphere via heating and ionization changes which produce VLF signal perturbations known as early VLF events. Typically, early events recover in about 100 s, but a small subclass does not recover for many minutes, known as long-recovery early events (LORE). In this study, we identify LORE as a distinct category of early VLF events, whose signature may occur either on its own or alongside the short-lived typical early VLF event. Since LORE onsets coincide with powerful lightning strokes of either polarity (±), we infer that they are due to long-lasting ionization changes in the uppermost D region ionosphere caused by electromagnetic pulses emitted by strong ± CG lightning peak currents of typically > 250 kA, which are also known to generate elves. The LORE perturbations are detected when the discharge is located within~250 km from the great circle path of a VLF transmitter-receiver link. The probability of occurrence increases with stroke intensity and approaches unity for discharges with peak currents ≥~300 kA. LOREs are nighttime phenomena that occur preferentially, at least in the present regional data set, during winter when strong ± CG discharges are more frequent and intense. The evidence suggests LORE as a distinct signature representing the VLF fingerprint of elves, a fact which, although was predicted by theory, it escaped identification in the long-going VLF research of lightning effects in the lower ionosphere.Citation: Haldoupis, C., M. Cohen, E. Arnone, B. Cotts, and S. Dietrich (2013), The VLF fingerprint of elves:Step-like and long-recovery early VLF perturbations caused by powerful ±CG lightning EM pulses,

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Precipitation estimation from passive microwave radiometry based on physically based profile retrieval algorithms must be aided by a microphysical generator providing structure information on the lower portions of the cloud, consistent with the upper-cloud structures that are sensed. One of the sources for this information is mesoscale model simulations involving explicit or parameterized microphysics. Such microphysical information can be then associated to brightness temperature signatures by using radiative transfer models, forming what are referred to as cloud-radiation databases. In this study cloud-radiation databases from three different storm simulations involving two different mesoscale models run at cloud scales are developed and analyzed. Each database relates a set of microphysical profile realizations describing the space-time properties of a given precipitating storm to multifrequency brightness temperatures associated to a measuring radiometer. In calculating the multifrequency signatures associated with the individual microphysical profiles over model space-time, the authors form what are called brightness temperature model manifolds. Their dimensionality is determined by the number of frequencies carried by the measuring radiometer. By then forming an analogous measurement manifold based on the actual radiometer observations, the radiative consistency between the model representation of a rain cloud and the measured representation are compared. In the analysis, the authors explore how various microphysical, macrophysical, and environmental factors affect the nature of the model manifolds, and how these factors produce or mitigate mismatch between the measurement and model manifolds. Various methods are examined that can be used to eliminate such mismatch. The various cloud-radiation databases are also used with a simplified profile retrieval algorithm to examine the sensitivity of the retrieved hydrometeor profiles and surface rainrates to the different microphysical, macrophysical, and environmental factors of the simulated storms. The results emphasize the need for physical retrieval algorithms to account for a number of these factors, thus preventing biased interpretation of the rain properties of precipitating storms, and minimizing rms uncertainties in the retrieved quantities.

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